Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/jl-cmd/claude-dev-env/pr-cleanupnpx skills add jl-cmd/claude-dev-env --skill pr-cleanupgit clone --depth 1 https://github.com/jl-cmd/claude-dev-envWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jl-cmd/claude-dev-env/pr-cleanup)<a href="https://agentmods.dev/skills/jl-cmd/claude-dev-env/pr-cleanup"><img src="https://agentmods.dev/badge/skills/jl-cmd/claude-dev-env/pr-cleanup.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00064 | $0.01344 |
| Opus 5 | $0.00032 | $0.00672 |
| Sonnet 5 | $0.00013 | $0.00269 |
| Haiku 4.5 | $0.00006 | $0.00134 |
Grade A, and why
pr-cleanup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PR cleanup
Contents
- Principle
- When this applies
- Composition
- Task seeding
- Process
- Promotion gates
- Finish report
- File index
Principle
One coding agent owns the cleanup outcome. pr-refinement coordinates parallel
preflight audits and produces findings, tested proposals, a combined change map,
and a delivery decision for the cleanup owner. Parent-to-child promotion uses
exact commit ancestry and fresh child-head checks.
When this applies
Use this skill for a pull request that needs placement review, capability naming, cleanup convergence, and a focused delivery boundary.
Required input: a pull request URL, number, or branch. If the target is missing,
respond exactly: Give a GitHub PR number, URL, or branch for pr-cleanup.
Use the repository that owns the target pull request. Keep every pull request in draft state until its applicable Ready gate is complete. Keep merge authority with the user.
Composition
| Skill | Role | Evidence |
|---|---|---|
pr-refinement |
Run the parallel audits, combine findings, and coordinate implementation shape | Change map and delivery decision |
pr-shared-extraction |
Find reusable behavior that belongs in shared_utils |
Placement findings and tested proposal |
pr-name-by-capability |
Find driver or motive words on reusable capability surfaces | Naming findings and rename directions |
pr-small-cl |
Choose one coherent pull request or an ordered replacement stack | Focused boundary and dependencies |
source-command-sr-loop |
Run e-simplify, then e-code-review low --fix until clean |
Review passes, fixes, and validation |
pr-summarizer (repo-local) |
When the repository under cleanup ships .claude/skills/pr-summarizer/, run it after Ready and post the secret-gist preview comment |
Preview URL and comment confirmation |
Task seeding
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 141 lines · 64 tokens per session scan A e6f6d2f35da7
pr-cleanup is a skill published in the GitHub repository jl-cmd/claude-dev-env (5 stars, last pushed today), licensed MIT. It adds 64 tokens to every session and 1,344 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
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